Question 1

How do I migrate an existing project from poetry to uv?

Accepted Answer

Start by using uv's pip-compatible interface with `uv pip` commands or initialize a new project with `uv init` and manually transfer dependencies. The documentation provides guides for transitioning workflows, but some poetry-specific features may require adaptation.

Question 2

Is uv really 100 times faster than pip for large dependency trees?

Accepted Answer

Yes, uv's benchmarks demonstrate 10-100x speed improvements in dependency resolution and installation, especially with warm caches, due to its Rust implementation and efficient algorithms. This makes it significantly faster for complex projects like those with many transitive dependencies.

Question 3

Can uv work with conda environments or should I use both tools?

Accepted Answer

uv does not manage Conda environments directly; it focuses on pip-based packages and Python versions. You might use Conda for environment creation and uv within those environments, but integration is limited, so it's not ideal for Conda-centric workflows.

Question 4

How to install and run a CLI tool like black with uv?

Accepted Answer

Use `uvx black` to run it ephemerally or `uv tool install black` for permanent installation, similar to pipx. This creates isolated environments to avoid dependency conflicts, and tools are cached globally for efficiency.

Question 5

uv vs rye: which one is better for new Python projects?

Accepted Answer

Both aim to unify Python tooling, but uv is faster and backed by Astral (creators of Ruff), with a focus on performance. Rye is another alternative; choose uv if speed and integration with Astral's ecosystem are priorities, while rye might appeal to those preferring a different approach.

Question 6

Does uv support private package repositories like Artifactory?

Accepted Answer

Yes, uv supports custom package indexes and private repositories through configuration files or environment variables, similar to pip. You can set index URLs and authentication details for seamless integration with internal PyPI servers.

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